K-mappings and regression trees

When
Start: 11/20/2013 - 1:15pm
End  : 11/20/2013 - 2:15pm

Category
Applied Math Seminar

Speaker
Yi Grace Wang (Duke University)

Abstract

I will describe a method for learning a piecewise affine approximation to a mapping f : R^d → R^p given a labeled training set of examples {x1, ..., xn} = X \subset R^d and targets {y1 = f(x1), ..., yn = f(xn)} = Y \subset R^p. The method first trains a binary subdivision tree that splits via hyperplanes in X corresponding to high variance directions in Y . A fixed number K of affine regressors of rank q are then trained via a K-means like iterative algorithm on the leaves of the tree. Expereiments are followed to evaluate its performance.

Where
Davidson, CMC